公开(公告)号：US20230350001A1

公开(公告)日：2023-11-02

申请号：US17661538

申请日：2022-04-29

Applicant: QUALCOMM Incorporated

Inventor： Mohammed Ali Mohammed HIRZALLAH ,  Xiaoxia ZHANG ,  Roohollah AMIRI ,  Srinivas YERRAMALLI ,  Marwen ZORGUI ,  Mohammad Tarek FAHIM ,  Taesang YOO ,  Rajat PRAKASH

IPC: G01S5/02 ,  H04W64/00 ,  H04L5/00 ,  G06N3/08

CPC classification number: G01S5/0236 ,  H04W64/00 ,  H04L5/0048 ,  G06N3/08 ,  G01S5/02521

Abstract: Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) receives one or more positioning assistance data messages for a downlink radio frequency fingerprint (DL-RFFP) positioning procedure from a first network entity, the one or more positioning assistance data messages including at least one parameter related to a machine learning model the UE is configured to use for the DL-RFFP positioning procedure, and transmits one or more location information messages to a second network entity, the one or more location information messages including one or more parameters related to the DL-RFFP positioning procedure.

公开(公告)号：US20230319617A1

公开(公告)日：2023-10-05

申请号：US18015683

申请日：2021-08-13

Applicant: QUALCOMM Incorporated

Inventor： Alexandros MANOLAKOS ,  Pavan Kumar VITTHALADEVUNI ,  Taesang YOO ,  June NAMGOONG ,  Jay Kumar SUNDARARAJAN ,  Naga BHUSHAN ,  Krishna Kiran MUKKAVILLI ,  Tingfang JI ,  Hwan Joon KWON ,  Wanshi CHEN

IPC: H04W24/10 ,  G06N3/08

CPC classification number: H04W24/10 ,  G06N3/08

Abstract: A first wireless device, such as a user equipment, generates a message indicating a processing time for at least one of training a neural network for channel state information (CSI) derivation or for reporting the CSI based on a trained neural network. The first wireless device transmits the message indicating the processing time to a second wireless device. The second wireless device may be a network entity, such as a base station, a transmission reception point, or another UE.

公开(公告)号：US20230275787A1

公开(公告)日：2023-08-31

申请号：US18004267

申请日：2021-08-13

Applicant: QUALCOMM Incorporated

Inventor： Pavan Kumar VITTHALADEVUNI ,  Alexandros MANOLAKOS ,  Taesang YOO ,  Naga BHUSHAN ,  June NAMGOONG ,  Jay Kumar SUNDARARAJAN ,  Hwan Joon KWON ,  Krishna Kiran MUKKAVILLI ,  Tingfang JI

IPC: H04L25/02 ,  G06N3/045

CPC classification number: H04L25/0254 ,  G06N3/045

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first device may transmit a neural network capability indication that indicates a capability of the first device associated with training at least one channel state feedback (CSF) neural network for facilitating providing CSF. The first device may receive, based at least in part on the capability of the first device, a CSF neural network configuration that indicates at least one parameter associated with the at least one CSF neural network. Numerous other aspects are provided.

公开(公告)号：US20230262568A1

公开(公告)日：2023-08-17

申请号：US17651165

申请日：2022-02-15

Applicant: QUALCOMM Incorporated

Inventor： Mohamed Fouad Ahmed MARZBAN ,  Wooseok NAM ,  Tao LUO ,  Arumugam CHENDAMARAI KANNAN ,  Vinay CHANDE ,  Taesang YOO

IPC: H04W36/32 ,  H04W36/00

CPC classification number: H04W36/32 ,  H04W36/00835 ,  H04W36/0058 ,  H04W36/00837

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first network entity may generate cell information about a first cell provided at least in part by the first network entity, the cell information associated with one or more potential sources of interference at a second cell provided at least in part by a second network entity, the one or more potential sources of interference being associated with the first cell. The first network entity may communicate the cell information to the second network entity. Numerous other aspects are described.

公开(公告)号：US20230246694A1

公开(公告)日：2023-08-03

申请号：US18003567

申请日：2021-08-13

Applicant: QUALCOMM Incorporated

Inventor： Pavan Kumar VITTHALADEVUNI ,  Alexandros MANOLAKOS ,  Taesang YOO ,  Naga BHUSHAN ,  June NAMGOONG ,  Jay Kumar SUNDARARAJAN ,  Krishna Kiran MUKKAVILLI ,  Hwan Joon KWON ,  Tingfang JI

IPC: H04B7/06 ,  H04B7/0456 ,  H04L5/00

CPC classification number: H04B7/0645 ,  H04B7/0478 ,  H04L5/0057 ,  H04B7/0626 ,  G06N3/045

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first device may receive an indication to use a first number of bits to report neural network based channel state information feedback (CSF). The first device may transmit, using a second number of bits that is different from the first number of bits, a report that indicates the CSF to a second device. Numerous other aspects are provided.

公开(公告)号：US20230180152A1

公开(公告)日：2023-06-08

申请号：US17544581

申请日：2021-12-07

Applicant: QUALCOMM Incorporated

Inventor： Eren BALEVI ,  Taesang YOO ,  Tao LUO ,  Srinivas YERRAMALLI ,  Junyi LI ,  Hamed PEZESHKI

IPC: H04W52/50 ,  H04W52/36 ,  H04W52/24 ,  H04W52/22 ,  H04W4/06

CPC classification number: H04W52/50 ,  H04W52/36 ,  H04W52/242 ,  H04W52/225 ,  H04W4/06

Abstract: A parameter server located at a base station may coordinate federated learning among multiple user equipment (UEs) using over-the-air (OTA) aggregation with power control to mitigate aggregation distortion due to amplitude misalignment. The parameter server may select a first group of UEs for a first OTA aggregation session of a federated learning round based on a common received power property of each UE in the first group of UEs. The parameter server may transmit a global model to the first group of UEs. Each UE in the first group may train the global model based on a local dataset and transmit values associated with the trained local model. The parameter server may receive, on resource elements for the first group of UEs, a first aggregate amplitude modulated analog signal representing a combined response from the first group of UEs.

公开(公告)号：US20230136354A1

公开(公告)日：2023-05-04

申请号：US17452697

申请日：2021-10-28

Applicant: QUALCOMM Incorporated

Inventor： June NAMGOONG ,  Yang YANG ,  Hyojin LEE ,  Taesang YOO

IPC: H04W24/10 ,  H04B7/0456 ,  H04W72/04 ,  H04L5/00

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a transformer configuration that includes a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more computation tasks of a plurality of computation tasks associated with a transformer-based cross-node machine learning system. The UE may transmit the at least one latent vector based at least in part on instantiating the transmitter neural network. Numerous other aspects are described.

公开(公告)号：US20230136038A1

公开(公告)日：2023-05-04

申请号：US17516321

申请日：2021-11-01

Applicant: QUALCOMM Incorporated

Inventor： Mohamed Fouad Ahmed MARZBAN ,  Wooseok NAM ,  Tao LUO ,  Taesang YOO ,  Arumugam CHENDAMARAI KANNAN ,  Hamed PEZESHKI ,  Mahmoud TAHERZADEH BOROUJENI

IPC: H04W24/02 ,  H04W72/08

Abstract: Aspects of the present disclosure include methods, apparatuses, and computer readable media for receiving interference information relating to at least one of a scheduling granularity, a subcarrier spacing, a scheduler type, resource utilization, a number of active UEs, a number of active beams, an elevation and an azimuth angle of each of the number of active beams, a synchronization signal block index, or a semi-persistent scheduling configuration associated with at least one neighbor base station (BS), estimating or predicting, based on the interference information received, an interference power profile caused by the at least one neighbor BS, receiving at least one of data information or control information, and decoding the at least one of the data information or the control information based on the interference power profile.

公开(公告)号：US20230084883A1

公开(公告)日：2023-03-16

申请号：US17898180

申请日：2022-08-29

Applicant: QUALCOMM Incorporated

Inventor： Hamed PEZESHKI ,  Tao LUO ,  Taesang YOO ,  Mahmoud TAHERZADEH BOROUJENI ,  Eren BALEVI ,  Srinivas YERRAMALLI ,  Junyi LI

IPC: H04L5/00 ,  H04W72/12 ,  H04W24/02

Abstract: Aspects presented herein may enable a network entity to configure a group of UEs to simultaneously transmit reference signals and to simultaneously transmit gradient vectors to the network entity, such that the network entity may receive the gradient vectors from the group of UEs as an aggregated gradient vector over the air. In one aspect, a base transmits, to a group of UEs, a configuration that configures the group of UEs to simultaneously transmit one or more group-common reference signals and to simultaneously transmit one or more gradient vectors associated with a federated learning procedure. The network entity receives, from the group of UEs, the one or more group-common reference signals and the one or more gradient vectors based on the configuration via multiple channels. The network entity calculates an average gradient vector based on the one or more group-common reference signals and the one or more gradient vectors.

公开(公告)号：US20230084164A1

公开(公告)日：2023-03-16

申请号：US17801505

申请日：2020-04-17

Applicant: Bo CHEN ,  Pavan Kumar THALADEVUNI ,  Taesang YOO ,  Naga BHUSHAN ,  Jay Kumar SUNDARARAJAN ,  Ruifeng MA ,  June NAMGOONG ,  Krishna Kiran MUKKAVILLI ,  Tingfang JI ,  Hao XU ,  QUALCOMM Incorporated

Inventor： Bo CHEN ,  Pavan Kumar VITTHALADEVUNI ,  Taesang YOO ,  Naga BHUSHAN ,  Jay Kumar SUNDARARAJAN ,  Ruifeng MA ,  June NAMGOONG ,  Krishna Kiran MUKKAVILLI ,  Hao XU ,  Tingfang JI

IPC: H04B7/06

Abstract: A method of wireless communication, by a user equipment (UE), includes receiving multiple neural network training configurations for channel state feedback (CSF). Each configuration corresponds to a different neural network framework. The method also includes training each of a group of neural network decoder/encoder pairs in accordance with the received training configurations. A method of wireless communication, by a base station, includes transmitting multiple neural network training configurations to a user equipment (UE) for channel state feedback (CSF). Each configuration corresponds to a different neural network framework. The method also includes receiving a neural network decoder/encoder pair trained in accordance with the training configurations.